CN115107782A - Electric automobile driving mode determination method and system and electric automobile - Google Patents
Electric automobile driving mode determination method and system and electric automobile Download PDFInfo
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- CN115107782A CN115107782A CN202110286492.5A CN202110286492A CN115107782A CN 115107782 A CN115107782 A CN 115107782A CN 202110286492 A CN202110286492 A CN 202110286492A CN 115107782 A CN115107782 A CN 115107782A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W40/09—Driving style or behaviour
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Abstract
The invention discloses a driving mode determining method of an electric automobile, a driving mode determining system of the electric automobile, the electric automobile and electronic equipment, wherein the driving mode determining method of the electric automobile comprises the following steps: after entering a self-defined driving mode learning process, acquiring driving characteristic data; after the driving characteristic data is acquired, determining the driving style of the driver based on the driving characteristic data; selecting a target power output curve matched with the driving style from a plurality of pre-stored power output curves according to the driving style, wherein the power output curve comprises a corresponding relation between the opening degree of an accelerator and the requested torque; and obtaining the self-defined driving mode according to the target power output curve. The driving mode determining method can realize the autonomous learning function of the vehicle, so that more driving modes are obtained, more individualized driving requirements of a vehicle driver are met, the driving experience of the driver is improved, and the scientific and technological sense of the vehicle is improved.
Description
Technical Field
The invention relates to the technical field of vehicles, in particular to a driving mode determining method of an electric automobile, a driving mode determining system of the electric automobile, the electric automobile and electronic equipment.
Background
The traditional vehicle driving style is locked and cannot be changed according to the actual needs of a driver, so that the individualized driving requirements of the driver cannot be met, the driving experience of the driver is poor, and an improvement space exists.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the above-mentioned problems in the prior art. Therefore, the driving mode determining method of the electric automobile can achieve the autonomous learning function of the automobile, so that more driving modes are obtained, more individualized driving requirements of the automobile driver are met, the driving experience of the driver is improved, and the technological sense of the automobile is improved.
The invention further provides a driving mode determining system of the electric automobile.
The invention also provides an electric automobile with the driving mode determining system of the electric automobile.
The invention also provides the electronic equipment.
The invention also proposes a non-transitory computer-readable storage medium.
The driving mode determining method of the electric vehicle according to the embodiment of the invention comprises the following steps: after entering a self-defined driving mode learning process, acquiring driving characteristic data; after the driving characteristic data is acquired, determining the driving style of the driver based on the driving characteristic data; selecting a target power output curve matched with the driving style from a plurality of pre-stored power output curves according to the driving style, wherein the power output curve comprises a corresponding relation between the opening degree of an accelerator and the requested torque; and obtaining the self-defined driving mode according to the target power output curve.
According to the driving mode determining method of the electric automobile, the autonomous learning function of the automobile can be achieved, so that more driving modes are obtained, the more individualized driving requirements of the automobile driver are met, the driving experience of the driver is improved, and the technological sense of the automobile is improved.
In addition, the method for determining the driving mode of the electric vehicle according to the embodiment of the invention may further have the following additional technical features:
according to some embodiments of the invention, after entering the custom driving mode learning process, obtaining driving characteristic data includes: the method comprises the steps of obtaining driving characteristic data in preset learning time, wherein the driving characteristic data comprises the time length of a plurality of accelerator opening intervals, the accelerator change rate in the accelerator opening intervals, the running time of a plurality of vehicle speed sections and a plurality of vehicle speed sections, the turn-on times of a steering lamp, the rotation information of a steering wheel, the braking times and the braking pressure of each brake.
According to some embodiments of the present invention, determining the driving style of the driver based on the driving characteristic data after the driving characteristic data is completely acquired comprises: obtaining the driving habits of the driver according to the time lengths of the accelerator opening intervals, the accelerator change rates in the accelerator opening intervals, the running time of a plurality of vehicle speed sections and a plurality of vehicle speed sections, the turn-on times of a steering lamp, the rotation information of a steering wheel, the braking times and the braking pressure of each braking; determining a driving style of the driver based on the driving habits of the driver.
According to some embodiments of the present invention, before determining the driving style of the driver based on the driving characteristic data after the driving characteristic data is completely acquired, the method further includes: and counting the acquired driving characteristic data, and judging whether the driving characteristic data is acquired completely according to a counting result.
According to some embodiments of the present invention, the driving characteristic data acquisition is completed when the following conditions are satisfied, including: the maximum vehicle speed is at least greater than or equal to a preset vehicle speed; the accelerator opening change interval is between the minimum opening and the maximum opening; at least a predetermined number of vehicle launch procedures; at least a predetermined number of vehicle braking processes; at least a predetermined number of vehicle steering events; different throttle opening interval positions for at least a predetermined time.
According to some embodiments of the invention, the driving mode determination method further comprises: and selecting the stored user-defined driving mode, and controlling the vehicle to run according to the user-defined driving mode.
The invention further provides a driving mode determining system of an electric vehicle, comprising: the acquisition module is used for acquiring driving characteristic data after entering a user-defined driving mode learning process; the driving style determining module is used for determining the driving style of a driver based on the driving characteristic data after the driving characteristic data is acquired; the selection module is used for selecting a target power output curve matched with the driving style from a plurality of pre-stored power output curves according to the driving style, wherein the power output curve comprises a corresponding relation between the accelerator opening and the requested torque; and the user-defined driving mode determining module is used for obtaining the user-defined driving mode according to the target power output curve.
According to another aspect of the present invention, an electric vehicle includes the driving mode determination system of the electric vehicle described above.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the driving mode determining method of the electric automobile.
The invention also proposes a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the driving mode determination method of an electric vehicle as described above.
Drawings
Fig. 1 is a flowchart of a driving mode determining method of an electric vehicle according to an embodiment of the present invention;
FIG. 2 is a functional diagram of a driving mode determination system according to one embodiment of the present invention;
FIG. 3 is a schematic illustration of a target power output curve for one embodiment of the present invention;
fig. 4 is a schematic configuration diagram of a driving mode determination system according to an embodiment of the present invention.
Reference numerals:
the driving mode determining system 100, the obtaining module 10, the driving style determining module 20, the selecting module 30 and the customized driving mode determining module 40.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are used merely for convenience of description and simplification of the description, but do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, are not to be construed as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically connected, electrically connected or can communicate with each other; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood according to specific situations by those of ordinary skill in the art.
In the present invention, unless expressly stated or limited otherwise, the recitation of a first feature "on" or "under" a second feature may include the recitation of the first and second features being in direct contact, and may also include the recitation that the first and second features are not in direct contact, but are in contact via another feature between them. Also, the first feature "on," "above" and "over" the second feature may include the first feature being directly above and obliquely above the second feature, or simply indicating that the first feature is at a higher level than the second feature. "beneath," "under" and "beneath" a first feature includes the first feature being directly beneath and obliquely beneath the second feature, or simply indicating that the first feature is at a lesser elevation than the second feature.
A driving mode determination method of an electric vehicle according to an embodiment of the present invention is described below with reference to fig. 1 to 3.
Fig. 1 is a flowchart of a detection method of a vehicle according to an embodiment of the present invention, as shown in fig. 1, the detection method including:
in the embodiment of the invention, a user can enter a self-defined driving mode learning process through an EHU (vehicle-mounted large screen controller). Specifically, the user controls the EHU controller to transmit a signal entering a custom driving mode learning process to the VCU (vehicle control unit) by clicking a "user-defined driving mode" icon on the EHU.
Further, before the step S101 in the embodiment shown in fig. 1, the VCU first needs to forcibly switch the current driving mode of the vehicle to the NORMAL mode, and the vehicle will enter the custom driving mode learning process based on the NORMAL mode. Where the NORMAL mode is the target power output curve of code D in FIG. 3, the torque in NORMAL mode is linear with accelerator opening.
S101, after entering a user-defined driving mode learning process, acquiring driving characteristic data.
Further, on the basis of the embodiment shown in fig. 1, the step S101 may specifically include:
the method comprises the steps of obtaining driving characteristic data in preset learning time, wherein the driving characteristic data comprises the time length of a plurality of accelerator opening intervals, the accelerator change rate in the accelerator opening intervals, the running time of a plurality of vehicle speed sections and a plurality of vehicle speed sections, the turn-on times of a steering lamp, the rotation information of a steering wheel, the braking times and the braking pressure of each brake.
In the embodiment of the present invention, as shown in fig. 2, the specific manner of acquiring the collected driving characteristic data is; the VCU is used for collecting the time lengths of a plurality of accelerator opening intervals transmitted by the accelerator pedal and the accelerator change rate in the accelerator opening intervals so as to reflect the speed of the driver stepping on the accelerator. The plurality of accelerator opening intervals can be specifically divided into three accelerator opening intervals, and specifically can be as follows: small throttle opening (0-30%), medium throttle opening (30-65%) and large throttle opening (65-100%). The driving time of a plurality of vehicle speed sections and a plurality of vehicle speed sections transmitted by the ESC (electronic stability system controller) is collected by the VCU to reflect the driving environment of the vehicle. Specifically, the speed range may be divided into 0-40km/h, 40-60 km/h, 60-80 km/h, 80-100km/h, with durations greater than 100km/h recorded in the 80-100km/h speed range. The turn-on times of the steering lamp transmitted by the BCM (body controller) are collected by the VCU to assist in recording the overtaking habit of the driver, and the rotation information of the steering wheel transmitted by the ESC, namely the times of steering wheel turning or the times of turning larger than a calibration value, can assist in recording the overtaking habit of the driver together. The VCU collects the braking times transmitted by the brake pedal, and the VCU collects the braking pressure of each braking transmitted by the ESC, namely the master cylinder pressure during braking, so as to judge whether the driver has frequent braking, sudden braking or sudden acceleration and sudden deceleration driving style.
Further, after the step S101 and before the step S102 in the embodiment shown in fig. 1, the acquired driving characteristic data is counted first, and whether the acquisition of the driving characteristic data is completed is determined according to the counting result.
When the following conditions are satisfied, the acquisition of the driving characteristic data is completed, including: the maximum vehicle speed is at least greater than or equal to a preset vehicle speed; the accelerator opening change interval is between the minimum opening and the maximum opening; at least a predetermined number of vehicle take offs; at least a predetermined number of vehicle braking processes; at least a predetermined number of vehicle steering events; different throttle opening interval positions for at least a predetermined time.
Specifically, the following conditions are required to be satisfied for the completion of the acquisition of the driving characteristic data: the highest vehicle speed is at least greater than or equal to 100km/h so as to ensure that all vehicle speed sections are learned; the accelerator opening change interval covers all positions from 0 to 100 percent, namely, the driver has driving actions from no accelerator stepping to bottom in the driving process; at least 10 vehicle take offs (calibration); at least 10 (calibrated) vehicle braking processes; at least 10 (calibrated) vehicle steering events; a minor throttle opening (0-30%) position of at least 20 minutes (calibrated value); position of opening of middle throttle valve (30% -65%) for at least 20 min (calibration value); at least 20 minutes (calibration value) of large throttle opening (65% -100%) position.
And S102, after the driving characteristic data is acquired, determining the driving style of the driver based on the driving characteristic data.
Further, on the basis of the embodiment shown in fig. 1, the step S102 may specifically include:
obtaining the driving habits of the driver according to the time lengths of the accelerator opening intervals, the accelerator change rates in the accelerator opening intervals, the running time of the vehicle speed sections, the turning times of the steering lamp, the rotation information of the steering wheel, the braking times and the braking pressure of each braking; the driving style of the driver is determined based on the driving habits of the driver.
For example, the driving style can be classified into a "people-vehicle-in-one" driving style of vehicle linear output power, a "riding dust-free" driving style of vehicle starting faster, a "soft" driving style suitable for urban traffic congestion, and a "overtaking" driving style.
And S103, selecting a target power output curve matched with the driving style from a plurality of pre-stored power output curves according to the driving style, wherein the power output curve comprises the corresponding relation between the accelerator opening and the requested torque.
The VCU internal memory has therein a plurality of power output curves as shown in fig. 3, and a target power output curve matching the driving style is selected from among the plurality of pre-stored power output curves according to the driving style. For example, a driver who is used to the "man-in-vehicle" driving style desires that the accelerator opening degree and the requested torque are in a linear relationship, where the accelerator is stepped on, the power follows, and a target power output curve matched with the "man-in-vehicle" driving style is a curve D, namely, the NORMAL mode; the driver who is in a driving style of 'riding dust' in a suburb or on a smooth expressway or is used to start faster wants to have strong power output by slightly stepping on an accelerator, and a target power output curve matched with the driving style of 'riding dust' is a curve A; under urban congested road conditions or a driver who is used to a 'soft' driving style wants to better control the vehicle speed, the power output of the front half section of the accelerator is slow, and a target power output curve matched with the power output curve is a curve G; in the overtaking process, the opening degree of the accelerator in the front half section is large, the power is output more strongly, the power output interruption of the accelerator is more gentle, the power output in the rear half section of the accelerator is faster, and the target power output curve matched with the overtaking driving style is a curve E.
And S104, obtaining a self-defined driving mode according to the target power output curve.
In the embodiment of the invention, the specific process of obtaining the user-defined driving mode according to the target power output curve is as follows; and the VCU sends the target power output curve obtained in the learning process to the EHU large screen, and the VCU names the target power output curve as the driving style 1 and sends the driving style 1 to the EHU large screen, and the driver clicks 'storage' through the EHU large screen to obtain the driving style 1 which is most suitable for the driving style of the driver.
According to some embodiments of the invention, the driving mode determination method further comprises: and selecting the stored user-defined driving mode, and controlling the vehicle to run according to the user-defined driving mode.
That is, when the driver drives the vehicle again, the set driving style is selected through the EHU large screen, and the VCU controls the driving mode of the vehicle to be shifted to the mode of the target power output curve saved in the current driving mode according to the driving style selected by the driver, and controls the vehicle to operate in this mode.
According to the method for determining the driving mode of the electric automobile, disclosed by the embodiment of the invention, the autonomous learning function of the automobile can be realized, so that more driving modes are obtained, the more individualized driving requirements of an automobile driver are met, the driving experience of the driver is further improved, and the technological sense of the automobile is improved.
For clarity of the above embodiments, the operation principle of the driving mode determining method of the electric vehicle according to the embodiment of the present invention is described in detail below with reference to fig. 4, where fig. 4 is a structural diagram of the driving mode determining system 100 of the electric vehicle according to an embodiment of the present invention, and as shown in fig. 4, the driving mode determining system 100 of the electric vehicle mainly includes:
the acquisition module 10 is used for acquiring driving characteristic data after entering a user-defined driving mode learning process; a driving style determination module 20 configured to determine a driving style of the driver based on the driving characteristic data after the acquisition of the driving characteristic data is completed; the selection module 30 is used for selecting a target power output curve matched with the driving style from a plurality of pre-stored power output curves according to the driving style, wherein the power output curve comprises a corresponding relation between the accelerator opening and the requested torque; and the user-defined driving mode determining module 40 is used for obtaining a user-defined driving mode according to the target power output curve.
The operation principle of the driving mode determining system 100 for an electric vehicle is as follows:
firstly, the obtaining module 10 obtains driving characteristic data, then the driving style determining module 20 determines the driving style of the driver according to the data obtained by the obtaining module 10, further, the selecting module 30 selects a target power output curve matched with the driving style from a plurality of pre-stored power output curves according to the driving style determined by the driving style determining module 20, and finally, the customized driving mode determining module 40 obtains a customized driving mode according to the matched target power output curve.
An electric vehicle according to another aspect of the present invention includes the driving mode determining system 100 of the electric vehicle described above. Other configurations for electric vehicles, such as transmissions, braking systems, steering systems, etc., are known in the art and are well known to those skilled in the art, and therefore, will not be described in detail herein.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the steps of the driving mode determining method of the electric vehicle are realized when the processor executes the program.
The invention also proposes a non-transitory computer-readable storage medium on which a computer program is stored which, when being executed by a processor, carries out the steps of the driving mode determination method of an electric vehicle as described above.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples described in this specification can be combined and combined by those skilled in the art.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A driving mode determination method of an electric vehicle, characterized by comprising:
after entering a self-defined driving mode learning process, acquiring driving characteristic data;
after the driving characteristic data is acquired, determining the driving style of the driver based on the driving characteristic data;
selecting a target power output curve matched with the driving style from a plurality of pre-stored power output curves according to the driving style, wherein the power output curve comprises a corresponding relation between the opening degree of an accelerator and the requested torque;
and obtaining the self-defined driving mode according to the target power output curve.
2. The method for determining the driving mode of the electric vehicle according to claim 1, wherein after entering the customized driving mode learning process, acquiring driving characteristic data comprises:
the method comprises the steps of obtaining driving characteristic data in preset learning time, wherein the driving characteristic data comprises the time length of a plurality of accelerator opening intervals, the accelerator change rate in the accelerator opening intervals, the running time of a plurality of vehicle speed sections and a plurality of vehicle speed sections, the turn-on times of a steering lamp, the rotation information of a steering wheel, the braking times and the braking pressure of each brake.
3. The method for determining the driving mode of the electric vehicle according to claim 2, wherein determining the driving style of the driver based on the driving characteristic data after the acquisition of the driving characteristic data is completed includes:
obtaining the driving habits of the driver according to the time lengths of the plurality of accelerator opening intervals, the accelerator change rates in the plurality of accelerator opening intervals, the running time of a plurality of vehicle speed sections and a plurality of vehicle speed sections, the turn-on times of a steering lamp, the rotation information of a steering wheel, the braking times and the braking pressure of each braking;
determining a driving style of the driver based on the driving habits of the driver.
4. The method of determining the driving mode of the electric vehicle according to claim 2, wherein before determining the driving style of the driver based on the driving characteristic data after the completion of the acquisition of the driving characteristic data, further comprising:
and counting the acquired driving characteristic data, and judging whether the driving characteristic data is acquired completely according to a counting result.
5. The driving mode determination method of an electric vehicle according to claim 4, wherein the driving characteristic data acquisition is completed when the following condition is satisfied, including:
the maximum vehicle speed is at least greater than or equal to a predetermined vehicle speed;
the accelerator opening change interval is between the minimum opening and the maximum opening;
at least a predetermined number of vehicle take offs;
at least a predetermined number of vehicle braking processes;
at least a predetermined number of vehicle steering events;
different throttle opening interval positions for at least a predetermined time.
6. The driving mode determination method of an electric vehicle according to claim 1, characterized by further comprising: and selecting the stored user-defined driving mode, and controlling the vehicle to run according to the user-defined driving mode.
7. A driving mode determination system of an electric vehicle, characterized by comprising:
the acquisition module is used for acquiring driving characteristic data after entering a user-defined driving mode learning process;
the driving style determining module is used for determining the driving style of a driver based on the driving characteristic data after the driving characteristic data is acquired;
the selection module is used for selecting a target power output curve matched with the driving style from a plurality of pre-stored power output curves according to the driving style, wherein the power output curve comprises a corresponding relation between the accelerator opening and the requested torque;
and the user-defined driving mode determining module is used for obtaining the user-defined driving mode according to the target power output curve.
8. An electric vehicle, comprising: the driving mode determination system of an electric vehicle according to claim 7.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method for determining a driving mode of an electric vehicle according to any one of claims 1 to 6 are implemented when the processor executes the program.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the driving mode determination method of an electric vehicle according to any one of claims 1 to 6.
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| CN202110286492.5A CN115107782A (en) | 2021-03-17 | 2021-03-17 | Electric automobile driving mode determination method and system and electric automobile |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102013001666A1 (en) * | 2013-01-31 | 2014-07-31 | Volkswagen Aktiengesellschaft | Method for driver-specific adjustment of adjustable components of vehicle, involves detecting driving behavior information of driver of vehicle, and automatic changing data set depending on detected driving behavior information |
| CN104828090A (en) * | 2014-12-09 | 2015-08-12 | 北汽福田汽车股份有限公司 | Vehicle control method, device and vehicle |
| US20180113461A1 (en) * | 2016-10-20 | 2018-04-26 | Magna Electronics Inc. | Vehicle control system that learns different driving characteristics |
| CN108248609A (en) * | 2016-12-29 | 2018-07-06 | 现代自动车株式会社 | Hybrid vehicle and the method that prediction drives pattern in hybrid vehicle |
| CN111376911A (en) * | 2018-12-29 | 2020-07-07 | 北京宝沃汽车有限公司 | Vehicle and driving style self-learning method and device thereof |
| CN111516693A (en) * | 2020-04-09 | 2020-08-11 | 吉利汽车研究院（宁波）有限公司 | Method for self-adapting driving mode and vehicle-mounted terminal |
| EP3750765A1 (en) * | 2019-06-14 | 2020-12-16 | Bayerische Motoren Werke Aktiengesellschaft | Methods, apparatuses and computer programs for generating a machine-learning model and for generating a control signal for operating a vehicle |
| US20210061288A1 (en) * | 2019-08-28 | 2021-03-04 | Toyota Motor North America, Inc. | Driver driving style detection and application system |
-
2021
- 2021-03-17 CN CN202110286492.5A patent/CN115107782A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102013001666A1 (en) * | 2013-01-31 | 2014-07-31 | Volkswagen Aktiengesellschaft | Method for driver-specific adjustment of adjustable components of vehicle, involves detecting driving behavior information of driver of vehicle, and automatic changing data set depending on detected driving behavior information |
| CN104828090A (en) * | 2014-12-09 | 2015-08-12 | 北汽福田汽车股份有限公司 | Vehicle control method, device and vehicle |
| US20180113461A1 (en) * | 2016-10-20 | 2018-04-26 | Magna Electronics Inc. | Vehicle control system that learns different driving characteristics |
| CN108248609A (en) * | 2016-12-29 | 2018-07-06 | 现代自动车株式会社 | Hybrid vehicle and the method that prediction drives pattern in hybrid vehicle |
| CN111376911A (en) * | 2018-12-29 | 2020-07-07 | 北京宝沃汽车有限公司 | Vehicle and driving style self-learning method and device thereof |
| EP3750765A1 (en) * | 2019-06-14 | 2020-12-16 | Bayerische Motoren Werke Aktiengesellschaft | Methods, apparatuses and computer programs for generating a machine-learning model and for generating a control signal for operating a vehicle |
| US20210061288A1 (en) * | 2019-08-28 | 2021-03-04 | Toyota Motor North America, Inc. | Driver driving style detection and application system |
| CN111516693A (en) * | 2020-04-09 | 2020-08-11 | 吉利汽车研究院（宁波）有限公司 | Method for self-adapting driving mode and vehicle-mounted terminal |
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